Today’s post is a scatter plot from Thomson Reuters looking at changes in global life expectancy since 1990. What is really nice about this piece is the main space for the data visualisation presents all of the data for all of the available countries. Beneath the main visualisation, the designer chose to use small multiples of the same chart to highlight broader regional trends.
Credit for the piece goes to, I think, Hwei Wen Foo. (Credit on the graphic is W. Foo.)
Well maybe not so much the space. Anyway, Nicolas Rapp, who does a lot of work for Fortune Magazine and previously the AP, created his first connected scatter plot. I have been a fan of them for quite some time and have been able to use them from time to time. Rapp’s scatter plot looks at the profits and revenues of the Fortune 500 in the last 20 years. But what I think makes his piece particularly strong are the two annotations he provides to explain the “loops” in the data: the two big recessions.
Credit for the piece goes to Nicolas Rapp.
Earlier this month the Federal Reserve Bank of New York published a report on household debt. Among the findings was the story that student debt is rising to problematic levels as it may act as a brake on economic recovery. In short, without an economy creating jobs for the young (recent university graduates) it becomes increasingly difficult for the young to pay pack the loans for the sharply rising costs of university tuition.
The report made this argument by use of interactive choropleth maps and charts. The one below looks at
But another chart that talks about the rising levels of student loan debt misses the mark. Here we see some rather flat lines. Clearly student loans are growing, but without a common baseline, the variations in the other types of debt muddle that message.
I took the liberty of using the data provided by the New York Fed and charting the lines all separately. Here you can clearly see just how in less than ten years, student loans have risen from $200 billion to $1,000 billion. This as credit card debt is falling along with other forms of debt (non-automotive).
The New York Fed did some great work, but with just one tweak to their visualisation forms, their story is made much more powerful and much more clear.
Credit for the original work goes to the Federal Reserve Bank of New York.
Yesterday I looked at the aboriginal Canadian identity infographic and wondered if bubbles in a bubble suffice for understanding size and relationship. Today we look at an interactive graphic from the Los Angeles Times where I do not think the bubbles suffice.
In this graphic, I cannot say the bubbles work. Besides the usual difficulty in comparing the sizes of bubbles, too many of the bubbles are spaced too far apart. These white gaps make it even more difficult to compare the bubbles. Furthermore, as you will see in a moment, it is difficult to see which programmes receive more than others because there is no ranking order to the bubbles.
Below is a quick data sketch of the state funds only data for 2013 and 2012.
While I did not spend a lot of time on it, you can clearly see how simply switching to a bar chart allows the user to see the rank of programmes by state funding. It is not a stretch to add some kind of toggle function as in the original. One of the tricky parts is the percent growth. You will note above that my screenshot highlights high speed rail; the growth was over 3000%. That is far too much to include in my graphic, so I compared the actuals instead. That is one of the tradeoffs, but in my mind it is an acceptable one.
Credit for the original goes to Paige St. John and Armand Emamdjomeh.
Continuing this week’s map theme, we have an example of a cartogram from the New York Times. This piece supplements an article about how some manufacturing companies are starting to look away from China as a place for their facilities. There are two maps, the first (not shown here) looks at economic output overall. The second (below) takes that output and accounts for population.
Hexagons are used instead of the more familiar squares to represent 500,000 people and the colour is the GDP per capita. The text accompanying the graphic explains how this is a measure of economic potential being (or not being) realised. But what the hexagons allow the map to do is better represent the shapes of the countries. Squares, more common in cartograms, create awkward box-like outlines of countries. That would be fine if countries were often shaped like squares, but they are not.
I am not often a fan of cartograms, but I find this one well executed and the annotations and explanatory text make what might otherwise be confusing far simpler to understand. All in all, a solid piece.
Credit for the piece goes to Mike Bostock and Keith Bradsher.
Today’s map comes from the Texas Tribune out of Austin, Texas. The map displays the location of disposal wells, i.e. the sites where the waste water from fracking and related drilling operations are dumped. Firstly, the map hints that the fracking industry is not spread equally across the state.
But secondly, the map does this through the use of hexagons that represent well density. So at a broad, state-wide view, the user sees almost a traditional choropleth. The difference is that these are not natural or political boundaries but rather data constructs designed to aggregate highly granular data points.
Even nicer, however, is that if you want to see where disposal wells are in your county or town, the map lets you do that too. Because as you zoom in ever closer, the individual wells appear within the hexagons that they colour. It’s a very solid piece of work.
Credit for the piece goes to Ryan Murphy.
Cyprus has been in the news over the course of this past week because its financial system almost brought the country to bankruptcy. And that has meant trouble for European markets. So now it’s time to look at the economies of Europe once again. And the National Post has done a great job using clear and concise small multiples to examine key metrics for the ten largest European economies—not necessarily EU economies mind you. But at the end of each row, they summed up the country’s outlook in just one or two sentences.
Credit for the piece goes to Richard Johnson, Grant Ellis, John Shmuel, and Andrew Barr.
The US imports a lot. But it does not export quite as much. The difference between those two figures is what is known as the balance of trade. Quartz looks at the US balance of trade not at an overall level, but between individual countries.
This is not one of my favourite pieces. For starters, while the overall figures are in the accompanying text, it would be useful to include total US imports and exports alongside the graphic as a point of reference.
Secondly, a long-standing issue I have is area comparisons. Sometimes they are needed and useful, a good example is a tree map. But in this piece, the circles do not add up to a recognisable whole. They also do not help when looking at individual countries and their historical trade values. A dotted outline of a circle shows the previous year’s trade. But more often than not, the trade level was so similar that the circles nearly overlap exactly.
The grouping and highlighting functionality hints at a useful application to explore US trade data, but the clumsiness of the circles renders that usefulness moot. .
Credit for the piece goes to David Yanofsky.
Reality is never what you think. Over at the Washington Post’s Wonkblog I found a post about a YouTube video looking at wealth inequality in the United States. It looks at a study that compared what Americans thought the distribution of wealth in the United States is vs. what they think is an ideal distribution. And then the video compares that to the actual distribution.
The video is rather solid and does a fairly good job at explaining its point. And those unsure about wealth inequality and how it is different from and sometimes more meaningful than income inequality should read the post along with the video.
Credit for the video goes to a YouTube user named Politizane.
We throw the word minion around at work quite often. So for your Friday enjoyment comes a graphic from Indexed that looks at minions vis-a-vis wages vs. compensation as well as whether a worker is busy vs. powerful.
Credit for the piece goes to Jessica Hagy.
